AI Can Build the Model — But Can It Keep It Right?
The silent flaw in “superhuman” spreadsheet agents, and why drift is the real danger.
Everyone’s losing their minds.
🚀 “AI just outperformed Goldman and McKinsey analysts!”
📈 “It builds full DCFs in minutes!”
🔥 “It’s 10x faster and kills fat-finger errors!”
We get it.
The demo was slick.
The output looked good.
The hype machine is on full blast.
But here’s the part nobody’s asking:
What happens to that spreadsheet next week?
Or next month?
Or after one assumption changes and the logic quietly breaks?
The Real Problem Isn’t Build — It’s Drift.
Anyone who’s actually used large models in the wild knows the truth:
Most spreadsheet errors don’t happen at build.
They happen over time.
Not from one big mistake.
But from slow, invisible decay.
A formula copied into the wrong tab.
A range that doesn’t extend with new rows.
An assumption that updates in one place… but not in the other 3 it’s supposed to.
Someone hits delete.
Someone adds a “quick fix.”
Nobody audits the logic.
And now the whole model’s lying to you.
That’s drift.
It’s the silent killer of decision quality — and AI agents haven’t solved it.
We’ve Trained AI to Be Confident — Not Cautious.
The danger isn’t just that the model might be wrong.
It’s that it sounds right.
It presents clean.
It speaks with certainty.
It gives you charts and summaries and tabs that look like magic.
But even one cell of quiet chaos can wreck the whole decision.
Until Drift Is Solved, Superhuman Isn’t Real.
This is the part most people miss.
Yes — AI can build the model faster.
Yes — it can write better formulas than your juniors.
Yes — it can save you time.
But the real test of any financial model isn’t whether it looks smart on Day 1.
It’s whether it holds up under pressure on Day 30.
The world doesn’t need faster models.
It needs trustworthy ones.
Until we solve for drift, we’re not replacing analysts.
We’re just shifting where the errors happen — and making them harder to see.
The Future of Modelling Is Not Just Speed — It’s Integrity.
Want to impress us?
Don’t just show us how fast the agent builds.
Show us how it audits.
How it version-controls.
How it tracks dependency chains and logic decay.
How it flags inconsistencies before they hit the CFO’s inbox.
Because a fast model is cool.
But a drifting model is dangerous.
And the real world doesn’t run on demos.
So What Is the Solution?
It’s not more speed.
It’s not prettier outputs.
It’s not ChatGPT in Excel with a nicer UI.
It’s drift-aware modelling.
A new standard that bakes auditability, traceability, and consistency into every layer of the stack.
Here’s what that looks like:
✅ Immutable Assumptions
Every assumption should be version-controlled and timestamped.
No more silent edits. No more “wait — who changed that?” moments.
If the assumptions move, you should know about it immediately.
✅ Live Dependency Mapping
Every output cell should carry a visible trail:
→ What inputs it relies on
→ What logic it applies
→ Where else it feeds
Like a living circuit diagram — so if one piece changes, the ripple effect is clear.
✅ Auto-Drift Alerts
The agent shouldn’t just build the model.
It should watch it.
If a formula range changes unexpectedly…
If a logic branch gets broken…
If an assumption is changed but not updated globally…
You get flagged — before the next board meeting.
✅ Narrative-Layer Thinking
AI agents should be trained to model stories, not just numbers.
Why does this input matter?
What’s the strategic implication of this scenario?
How does the logic map to the decision we’re actually making?
This is where real operators outperform both humans and machines:
They connect the spreadsheet to the story.
✅ Integrated Change Review
One button.
All the changes since last review.
Who changed what.
Why.
With a rollback option.
No more forensic audits on Friday night.
That’s the Future.
Not just “fast builds.”
But trustworthy, explainable, drift-resistant models — built by AI agents you can actually rely on.
And guess what?
The teams who get this right will not just outpace the Big 4.
They’ll replace them.
Because while everyone else is chasing speed…
The real edge is integrity at scale.